Geert Roelof van der Ploeg

PESCAR improves detection of subtle response-related patterns in multi-omics data by integrating response information into multiblock decomposition.

ACMTF-R integrates multi-omics data to identify shared and distinct outcome-associated variation, outperforming existing methods in simulated and real-world datasets.

This paper introduces PARAFAC for analyzing longitudinal microbiome data, demonstrating its effectiveness in identifying temporal patterns across three studies.

This study uses PARAFAC to analyze oral microbiome and metabolome dynamics during experimental gingivitis, identifying microbial subcommunities and metabolic pathways linked to inflammation.

The study shows that soil history has a greater impact than plant history on arbuscular mycorrhizal fungal community assembly in a grassland diversity experiment.